Admirals

GP: 7 | W: 3 | L: 1 | OTL: 3 | P: 9
GF: 17 | GA: 16 | PP%: 13.33% | PK%: 87.50%
DG: Danny Rhéaume | Morale : 50 | Moyenne d'Équipe : N/A
Prochain matchs #83 vs Monarchs
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Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SP
1Axel Jonsson-FjallbyX100.00766894666858595550485863554444605000
2Deven Sideroff (R)X100.00736395546348485250465163485252555000
3Lukas JasekX100.00746888616871755850516163584444635000
4Nicholas CaamanoX100.00794489637255785444585864254545624700
5Cody Glass (R)XX100.00634194806765617453646459254747665000
6Stefan NoesenXX100.00844577747559696437557161255859685000
7Taylor Raddysh (R)XX100.00838089638078836075536268594444655000
8Ryan MacInnis (R)X100.00714399647154805847605562254444615000
9Jordy Bellerive (R)X100.00726978676974795670495961564444614700
10Nick RitchieX100.00865844758467717529707161256364705000
11Ondrej KaseX100.00594191866874617333756462755960685000
12Sasha Chmelevski (R)XX100.00736884656865666278596263594444645000
13Henri JokiharjuX100.00764386826771846125524875255757635000
14Jacob LarssonX100.00674293777369855725514875256060625000
15Lucas CarlssonX100.00747084657073785425524262404444564700
16Michael Anderson (R)X100.00767189777163674925414161394444545000
17Brogan Rafferty (R)X100.00787292647264666025604565434444595000
18Leon Gawanke (R)X100.00767286637268725425524163394444554700
Rayé
1Manuel Wiederer (R)XX100.00716486616456585265534760454444555000
2Nathan Noel (R)XX100.00646366536349514455384454424444475000
3Riley Sutter (R)X100.00827499637452544850464564434444555000
4Keaton Thompson (R)X100.00736786676762665025444060384545535000
5Noah Dobson (R)X100.00694291807162636925534859254747605000
6Johnathan Kovacevic (R)X100.00787879637855584825384262404444524700
7Mac Hollowell (R)X100.00676279676262665025434257404444525000
MOYENNE D'ÉQUIPE100.0074608668706368574152526341484859490
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Adam Werner (R)100.0057597473596151605857304444575000
2Mikhail Berdin100.0059627863606351615857304444585000
Rayé
MOYENNE D'ÉQUIPE100.005861766860625161585730444458500
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ryan Huska66707368656082CAN463850,000$


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur Nom de l'ÉquipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Cody GlassAdmirals (ANA)C/RW715620011164516.67%013719.680332330001151038.40%12500000.8701000101
2Stefan NoesenAdmirals (ANA)LW/RW7156340911160106.25%113018.620226320000140033.33%2700000.9203000011
3Taylor RaddyshAdmirals (ANA)C/RW722424076951022.22%011216.14112332000010060.00%11000000.7101000010
4Ryan MacInnisAdmirals (ANA)C722420064100520.00%08011.5200003000000035.09%5700000.9900000011
5Ondrej KaseAdmirals (ANA)RW7404100191621025.00%316123.062025330001341041.03%7800000.5023000200
6Sasha ChmelevskiAdmirals (ANA)C/RW731424019161518.75%010715.42202631000001240.00%500000.7400000002
7Henri JokiharjuAdmirals (ANA)D7123-21407543225.00%216022.97101331000024000.00%000000.3700000000
8Lucas CarlssonAdmirals (ANA)D70333401044120.00%615622.38011331000027000.00%000000.3800000000
9Leon GawankeAdmirals (ANA)D703341401043000.00%511917.1300015000012000.00%000000.5000000000
10Jacob LarssonAdmirals (ANA)D7112-44051072514.29%716223.27011531000026000.00%000000.2500000000
11Michael AndersonAdmirals (ANA)D70223135561110.00%211716.850110800007000.00%000000.3400001000
12Nick RitchieAdmirals (ANA)LW702218018810290.00%215221.810004330001260020.00%1000000.2602000000
13Brogan RaffertyAdmirals (ANA)D70222140965010.00%514721.05000430000018000.00%000000.2700000000
14Axel Jonsson-FjallbyAdmirals (ANA)LW71012202681112.50%18812.59000000000900100.00%200000.2300000000
15Nicholas CaamanoAdmirals (ANA)RW71012003332533.33%18912.75000000000120022.22%900000.2200000010
16Deven SideroffAdmirals (ANA)RW7000-320132210.00%0608.6500004000010050.00%400000.0000000000
17Lukas JasekAdmirals (ANA)RW7000-300373030.00%0537.650000300000000.00%100000.0000000000
18Jordy BelleriveAdmirals (ANA)C7000-340363010.00%1497.0100000000000060.00%4000000.0000000000
Stats d'équipe Total ou en Moyenne12617304714915101118126267613.49%36208916.5969154234700032363244.66%46800000.45210001345
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien Nom de l'ÉquipeGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Mikhail BerdinAdmirals (ANA)42020.8941.68250007660100.571743010
2Adam WernerAdmirals (ANA)31110.8931.94186006560100.333334000
Stats d'équipe Total ou en Moyenne73130.8931.7943600131220200.5001077010


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Salaire RestantSalaire MoyenSalaire Moyen RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Adam WernerAdmirals (ANA)G231997-01-01Yes200 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Axel Jonsson-FjallbyAdmirals (ANA)LW221998-02-10No185 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Brogan RaffertyAdmirals (ANA)D251995-05-28Yes192 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Cody GlassAdmirals (ANA)C/RW211999-03-31Yes178 Lbs6 ft2NoNoNo3Pro & Farm1,713,333$1,713,333$1,713,333$1,713,333$0$0$No1,713,333$1,713,333$
Deven SideroffAdmirals (ANA)RW231997-04-14Yes171 Lbs5 ft11NoNoNo3Pro & Farm935,833$935,833$935,833$935,833$0$0$No935,833$935,833$
Henri JokiharjuAdmirals (ANA)D211999-06-17No180 Lbs6 ft0NoNoNo3Pro & Farm925,000$925,000$925,000$925,000$0$0$No925,000$925,000$Lien
Jacob LarssonAdmirals (ANA)D231997-04-29No195 Lbs6 ft2NoNoNo3Pro & Farm894,166$894,166$894,166$894,166$0$0$No894,166$894,166$Lien
Johnathan KovacevicAdmirals (ANA)D221997-07-12Yes207 Lbs6 ft4NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Jordy BelleriveAdmirals (ANA)C211999-05-02Yes194 Lbs5 ft11NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Keaton ThompsonAdmirals (ANA)D241995-09-14Yes182 Lbs6 ft0NoNoNo3Pro & Farm925,000$925,000$925,000$925,000$0$0$No925,000$925,000$
Leon GawankeAdmirals (ANA)D211999-05-31Yes198 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Lucas CarlssonAdmirals (ANA)D221997-07-05No190 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Lukas JasekAdmirals (ANA)RW221997-08-28No183 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Mac HollowellAdmirals (ANA)D211998-09-26Yes170 Lbs5 ft10NoNoNo3Pro & Farm799,766$799,766$799,766$799,766$0$0$No799,766$799,766$
Manuel WiedererAdmirals (ANA)C/RW231996-11-21Yes170 Lbs6 ft0NoNoNo3Pro & Farm736,667$736,667$736,667$736,667$0$0$No736,667$736,667$
Michael AndersonAdmirals (ANA)D211999-05-25Yes196 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Mikhail BerdinAdmirals (ANA)G221998-02-28No163 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Nathan NoelAdmirals (ANA)C/LW231997-06-21Yes174 Lbs5 ft11NoNoNo3Pro & Farm925,000$925,000$925,000$925,000$0$0$No925,000$925,000$
Nicholas CaamanoAdmirals (ANA)RW211998-10-07No194 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Nick RitchieAdmirals (ANA)LW241995-12-05No234 Lbs6 ft2NoNoNo3Pro & Farm1,498,925$1,498,925$1,498,925$1,498,925$0$0$No1,498,925$1,498,925$Lien
Noah DobsonAdmirals (ANA)D202000-01-07Yes183 Lbs6 ft4NoNoNo3Pro & Farm1,431,667$1,431,667$1,431,667$1,431,667$0$0$No1,431,667$1,431,667$
Ondrej KaseAdmirals (ANA)RW241995-11-08No185 Lbs6 ft0NoNoNo3Pro & Farm2,600,000$2,600,000$2,600,000$2,600,000$0$0$No2,600,000$2,600,000$Lien
Riley SutterAdmirals (ANA)RW201999-10-24Yes200 Lbs6 ft1NoNoNo3Pro & Farm894,167$894,167$894,167$894,167$0$0$No894,167$894,167$
Ryan MacInnisAdmirals (ANA)C241996-02-13Yes185 Lbs6 ft3NoNoNo3Pro & Farm874,125$874,125$874,125$874,125$0$0$No874,125$874,125$
Sasha ChmelevskiAdmirals (ANA)C/RW211999-06-09Yes187 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Stefan NoesenAdmirals (ANA)LW/RW271993-02-12No205 Lbs6 ft1NoNoNo3Pro & Farm450,000$450,000$450,000$450,000$0$0$No450,000$450,000$Lien
Taylor RaddyshAdmirals (ANA)C/RW221998-02-18Yes216 Lbs6 ft3NoNoNo3Pro & Farm894,166$894,166$894,166$894,166$0$0$No894,166$894,166$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2722.33190 Lbs6 ft12.111,055,475$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Nick RitchieCody GlassOndrej Kase35122
2Stefan NoesenTaylor RaddyshSasha Chmelevski30122
3Axel Jonsson-FjallbyRyan MacInnisNicholas Caamano25122
4Deven SideroffJordy BelleriveLukas Jasek10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jacob LarssonHenri Jokiharju35122
2Brogan RaffertyLucas Carlsson30122
3Michael AndersonLeon Gawanke25122
4Jacob LarssonHenri Jokiharju10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Nick RitchieCody GlassOndrej Kase60122
2Stefan NoesenTaylor RaddyshSasha Chmelevski40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jacob LarssonHenri Jokiharju60122
2Brogan RaffertyLucas Carlsson40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Ondrej KaseNick Ritchie60122
2Stefan NoesenCody Glass40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jacob LarssonHenri Jokiharju60122
2Brogan RaffertyLucas Carlsson40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Ondrej Kase60122Jacob LarssonHenri Jokiharju60122
2Nick Ritchie40122Brogan RaffertyLucas Carlsson40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Ondrej KaseNick Ritchie60122
2Stefan NoesenCody Glass40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jacob LarssonHenri Jokiharju60122
2Brogan RaffertyLucas Carlsson40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Nick RitchieCody GlassOndrej KaseJacob LarssonHenri Jokiharju
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Nick RitchieCody GlassOndrej KaseJacob LarssonHenri Jokiharju
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Deven Sideroff, Ryan MacInnis, Nicholas CaamanoDeven Sideroff, Ryan MacInnisNicholas Caamano
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Michael Anderson, Leon Gawanke, Brogan RaffertyMichael AndersonLeon Gawanke, Brogan Rafferty
Tirs de Pénalité
Ondrej Kase, Nick Ritchie, Stefan Noesen, Cody Glass, Taylor Raddysh
Gardien
#1 : Adam Werner, #2 : Mikhail Berdin


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
LigueDomicileVisiteur
# VS Équipe GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
1Condors200010014401000000112-11000100032130.750471100736330423942133811283013215.38%14378.57%08117646.02%9220544.88%368741.38%165113178569244
2Flames11000000532000000000001100000053221.0005813007363144239421311615107114.29%30100.00%08117646.02%9220544.88%368741.38%165113178569244
3Moose211000005411010000023-11100000031220.500591400736335423942133910263212325.00%12191.67%08117646.02%9220544.88%368741.38%165113178569244
4Sharks2000000235-21000000112-11000000123-120.500369007363474239421334922291300.00%11190.91%08117646.02%9220544.88%368741.38%165113178569244
Total72101003171613010000247-342001001139490.64317304700736312642394213122369110145613.33%40587.50%08117646.02%9220544.88%368741.38%165113178569244
_Since Last GM Reset72101003171613010000247-342001001139490.64317304700736312642394213122369110145613.33%40587.50%08117646.02%9220544.88%368741.38%165113178569244
_Vs Conference611010031213-13010000247-33100100186270.5831222340073631124239421311130769138513.16%37586.49%08117646.02%9220544.88%368741.38%165113178569244
_Vs Division71101003171613010000247-341001001139470.50017304700736312642394213122369110145613.33%40587.50%08117646.02%9220544.88%368741.38%165113178569244

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
79W3173047126122369110100
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
72110031716
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
301000247
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4201001139
Derniers 10 Matchs
WLOTWOTL SOWSOL
310003
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
45613.33%40587.50%0
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
423942137363
Mises en Jeu
Gagnées en Zone OffensiveTotal en Zone Offensive% Gagnées en Zone Offensive Gagnées en Zone DéfensiveTotal en Zone Défensive% Gagnées en Zone DéfensiveGagnées en Zone NeutreTotal en Zone Neutre% Gagnées en Zone Neutre
8117646.02%9220544.88%368741.38%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
165113178569244


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
2 - 2020-09-0411Condors2Admirals1LXXSommaire du Match
3 - 2020-09-0520Admirals2Sharks3LXXSommaire du Match
5 - 2020-09-0734Moose3Admirals2LSommaire du Match
6 - 2020-09-0844Sharks2Admirals1LXXSommaire du Match
7 - 2020-09-0947Admirals3Moose1WSommaire du Match
8 - 2020-09-1061Admirals5Flames3WSommaire du Match
10 - 2020-09-1275Admirals3Condors2WXSommaire du Match
11 - 2020-09-1383Monarchs-Admirals-
12 - 2020-09-1494Flames-Admirals-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
13 - 2020-09-1598Admirals-Monarchs-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
2 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 2,849,782$ 2,849,782$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 0$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 5 0$ 0$




LigueDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT